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proxy_activate_from_spec

Generate and activate an MCP server from an OpenAPI or GraphQL specification URL.

Instructions

Generate an MCP server from an OpenAPI/GraphQL spec and activate it.

Args: name: A unique name for this generated server spec_url: URL to the OpenAPI spec (JSON/YAML) or GraphQL endpoint spec_type: 'openapi' or 'graphql' eager: If True, mount the server immediately lean: If True, attempt to use LAP (https://lap.sh) to produce a dramatically leaner input spec before 40mcp generation (F-12 research slice). Falls back gracefully if LAP CLI not available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
leanNo
nameYes
eagerNo
spec_urlYes
spec_typeNoopenapi

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explains parameter-level behavior (eager mounts immediately, lean uses LAP with graceful fallback) but does not disclose broader behavioral traits such as permissions required, destructiveness (e.g., whether it overwrites existing servers), or what happens after activation. With no annotations, more transparency is expected.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at roughly 140 words with a lead sentence and a well-structured bullet list for arguments. Every sentence contributes value with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters, no annotations, and an output schema, the description covers input semantics well but lacks context on error handling, network requirements, and what the output represents. The output schema may compensate, but the description itself is only moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must and does fully explain all 5 parameters in a clear 'Args' section. It adds meaning beyond the schema by detailing the purpose of each parameter (e.g., 'spec_type' values, 'lean' LAP behavior, 'eager' immediate mounting).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Generate an MCP server from an OpenAPI/GraphQL spec and activate it.' It uses a specific verb and resource and distinguishes from siblings like proxy_activate_server, which activates an existing server rather than generating one from a spec.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

While the description implies the tool is used when you have a spec to generate a server, it does not explicitly state when to use this versus alternatives like proxy_activate_server. No explicit context for when-not-to-use or prerequisites are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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